Proactive Adaptive Traffic Signal Control, Coordinated with Countdown Timers

Urban traffic networks require sophisticated signal control strategies that adapt to real-time conditions while providing driver information through countdown timers. However, integrating countdown displays with adaptive traffic control presents a fundamental timing prediction challenge: adaptive systems typically make decisions 1-4 seconds before phase changes, while meaningful countdown displays require 10+ seconds of advance notice. A special "1.5 cycle" timing constraint is proposed within the model predictive control (MPC) framework to address this integration challenge, guaranteeing future phase sequences within the prediction horizon to enable countdown functionality while maintaining adaptive optimization benefits. The approach employs the Generalized ARZ (GARZ) macroscopic traffic flow model with data-fitted fundamental diagrams to predict network dynamics.A special target function is proposed to achieve uniform traffic distribution and efficient phase utilization. The MPC optimization uses the Nelder-Mead method with constraint handling for phase duration bounds. Validation experiments using SUMO microsimulation with RESCO benchmark scenarios demonstrate that the macroscopic model achieves sufficient prediction accuracy for control purposes. The integrated control system successfully operates countdown timers with adaptive signal optimization, achieving 10-15% improvements in queue length and delay compared to fixed-time control while providing enhanced driver information systems.